The Study of the Training Platform towards Thailand’s International Airlines Cabin Crew during the Pandemic of Covid-19
Bibliographic record
Abstract
The COVID-19 pandemic has put the airline business in a challenging position. It is one of the leading businesses with tremendous impacts from the pandemic. Although international airlines confront difficulties returning to typical situations, they still need to provide their cabin crew the training courses because they must always be ready to return to work. This study aimed to explore international airline cabin crew’s needs, problems, and experiences of training platforms during the pandemic of COVID-19. The key informant of five cabin crew was selected from the international airlines in Thailand. An interview approach was used to collect the data using an in-depth interview form which was then analyzed using content analysis. The findings revealed 1) the organization should identify the characteristics of trainers when conducting during the pandemic, 2) the organization should set the appropriate climate for online training classes during the pandemic, 3) the organization should clarify the differences between theoretical class and practical class during the pandemics, 4) the organization should learn from the difficulties in conducting the online training class during the pandemics, 5) the organization should identifying the difference between conducting theoretical class and practical class, 6) the organization should take it to the next level, and 7) everyone in the organization should consider it as the new normal in life as the cabin crew. The study summarized, then proposed the findings of the overall cabin crew’s needs, problems, and experiences of training platforms during the pandemic of COVID-19.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".